Volume 2 Number 3 (May 2013)

Extracting and Labelling the Objects from an Image by Using the Fuzzy Clustering Algorithm and a New Cluster Validity

Chien-Hsing Chou, Yi-Zeng Hsieh, Mu-Chun Su, and Yung-Long Chu

Abstract—Many real-world and man-made objects are line symmetry. To detection the line-symmetry objects from an image, in this paper, a new cluster validity measure which adopts a non-metric distance measure based on the idea of "line symmetry" is presented. The thresholding technique is first applied to extract the objects from the original image; and the object pixels are transferred to be the data patterns. Then the fuzzy clustering algorithm is applied to label the object pixels; and the proposed validity measure is used in determining the number of objects. Simulation results are used to illustrate the performance of the proposed measure.

Chien-Hsing Chou and Yung-Long Chu are with the Department of Electrical Engineering, Tamkang University, Taiwan (e-mail: chchou@mail.tku.edu.tw).
Yi-Zeng Hsieh and Mu-Chun Su are with the Department of Computer Science & Information Engineering, National Central University, Taiwan.

Cite:Chien-Hsing Chou, Yi-Zeng Hsieh, Mu-Chun Su, and Yung-Long Chu, "Extracting and Labelling the Objects from an Image by Using the Fuzzy Clustering Algorithm and a New Cluster Validity," International Journal of Computer and Communication Engineering vol. 2, no. 3, pp. 281-283, 2013.